



"""simple docstring"""







import argparse
import json

from tqdm import tqdm

def     UpperCAmelCase_					(				):




			'''simple docstring'''



			_lowerCamelCase					:					int	       =    argparse.ArgumentParser()

			# Required parameters
			parser.add_argument(
			    '--src_path'      ,							type=lowerCAmelCase__      ,							default='biencoder-nq-dev.json'      ,							help='Path to raw DPR training data'      ,							)
			parser.add_argument(
			    '--evaluation_set'      ,							type=lowerCAmelCase__      ,							help='where to store parsed evaluation_set file'      ,							)
			parser.add_argument(
			    '--gold_data_path'      ,							type=lowerCAmelCase__      ,							help='where to store parsed gold_data_path file'      ,							)
			_lowerCamelCase					:					List[Any]	       =    parser.parse_args()

			with open(args.src_path      ,							'r'						) as src_file, open(args.evaluation_set      ,							'w'						) as eval_file, open(
			    args.gold_data_path      ,							'w'						) as gold_file:
						_lowerCamelCase					:					Any	       =    json.load(lowerCAmelCase__						)
						for dpr_record in tqdm(lowerCAmelCase__						):
									_lowerCamelCase					:					Union[str, Any]	       =    dpr_record["""question"""]
									_lowerCamelCase					:					Dict	       =    [context["""title"""] for context in dpr_record["""positive_ctxs"""]]
									eval_file.write(question + '\n'						)
									gold_file.write('\t'.join(lowerCAmelCase__						) + '\n'						)


if __name__ == "__main__":
	main()










from typing import TYPE_CHECKING

from ...utils import _LazyModule


a      :  int			     =			{'tokenization_wav2vec2_phoneme': ['Wav2Vec2PhonemeCTCTokenizer']}


if TYPE_CHECKING:
	from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
	import sys

	a      :  int			     =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






